{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-03-23T15:16:22.983082Z",
     "start_time": "2020-03-23T15:16:22.521338Z"
    }
   },
   "outputs": [],
   "source": [
    "from sklearn.utils import shuffle\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "%matplotlib inline\n",
    "\n",
    "MAX_ITERATION = 10000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-03-23T15:16:23.731629Z",
     "start_time": "2020-03-23T15:16:23.704712Z"
    }
   },
   "outputs": [],
   "source": [
    "def data_generator(mean1, cov1, mean2, cov2, num):\n",
    "    np.random.seed(0)\n",
    "    X = np.random.multivariate_normal(mean1, cov1, num//2)\n",
    "    np.random.seed(1)\n",
    "    y = np.full(num//2, -1, dtype=int)\n",
    "    X_ = np.random.multivariate_normal(mean2, cov2, num-num//2)\n",
    "    y_ = np.full(num-num//2, 1, dtype=int)\n",
    "    X1 = np.concatenate((X, X_), axis=0)\n",
    "    y1 = np.concatenate((y, y_))\n",
    "\n",
    "    return shuffle(X1, y1)\n",
    "\n",
    "\n",
    "def drawer(X, y, w1, w2):\n",
    "    fig, ax = plt.subplots(1, 2, figsize=(15, 5))\n",
    "\n",
    "    for i in range(len(y)):\n",
    "        if y[i] == 1:\n",
    "            ax[0].scatter(X[i, 0], X[i, 1], c='r', marker='o')\n",
    "        else:\n",
    "            ax[0].scatter(X[i, 0], X[i, 1], c='b', marker='x')\n",
    "\n",
    "    l_x = np.linspace(np.min(X), np.max(X), X.shape[0])\n",
    "    l_y = -(w1[0]/w1[2]+w1[1]/w1[2]*l_x)\n",
    "    ax[0].plot(l_x, l_y)\n",
    "    xy_max = np.max(X, axis=0)\n",
    "    ax[0].set(xlim=(-xy_max[0]-1, xy_max[0]+1), ylim=(-xy_max[1]-1, xy_max[1]+1),\n",
    "              xlabel=\"x\",\n",
    "              ylabel=\"y\",\n",
    "              title=\"Perceptron Learning Algorithm\")\n",
    "\n",
    "    for i in range(len(y)):\n",
    "        if y[i] == 1:\n",
    "            ax[1].scatter(X[i, 0], X[i, 1], c='r', marker='o')\n",
    "        else:\n",
    "            ax[1].scatter(X[i, 0], X[i, 1], c='b', marker='x')\n",
    "\n",
    "    l_x = np.linspace(np.min(X), np.max(X), X.shape[0])\n",
    "    l_y = -(w2[0]/w2[2]+w2[1]/w2[2]*l_x)\n",
    "    ax[1].plot(l_x, l_y)\n",
    "    xy_max = np.max(X, axis=0)\n",
    "    ax[1].set(xlim=(-xy_max[0]-1, xy_max[0]+1), ylim=(-xy_max[1]-1, xy_max[1]+1),\n",
    "              xlabel=\"x\",\n",
    "              ylabel=\"y\",\n",
    "              title=\"Pocket Algorithm\")\n",
    "\n",
    "\n",
    "def perce_v1(X, y, w_init, max_iter):\n",
    "    w = w_init\n",
    "    X = np.concatenate((np.ones((X.shape[0], 1)), X), axis=1)\n",
    "\n",
    "    for i in range(max_iter):\n",
    "        h = np.sign(np.dot(X, w))\n",
    "        mistake_indices = np.where(h != y)[0]\n",
    "        mistake_num = len(mistake_indices)\n",
    "        if mistake_num > 0:\n",
    "            np.random.shuffle(mistake_indices)\n",
    "            j = np.random.choice(mistake_indices)\n",
    "            w = w + y[j]*X[j, :]\n",
    "        else:\n",
    "            break\n",
    "    h = np.sign(np.dot(X, w))\n",
    "    mistake_indices = np.where(h != y)[0]\n",
    "    mistake_num = len(mistake_indices)\n",
    "    print('Initial weight vector of Perceptron Learning Algorithm is', w_init)\n",
    "    print('Final weight vector of Perceptron Learning Algorithm is', w)\n",
    "    print('Accuracy of Perceptron Learning Algorithm is %.2f%%' %\n",
    "          (100*(X.shape[0]-mistake_num)/X.shape[0]))\n",
    "    return w\n",
    "\n",
    "\n",
    "def perce_v2(X, y, w_init, max_iter):\n",
    "    w = w_init\n",
    "    X = np.concatenate((np.ones((X.shape[0], 1)), X), axis=1)\n",
    "\n",
    "    for i in range(max_iter):\n",
    "        h = np.sign(np.dot(X, w))\n",
    "        mistake_indices = np.where(h != y)[0]\n",
    "        mistake_num = len(mistake_indices)\n",
    "        if mistake_num > 0:\n",
    "            np.random.shuffle(mistake_indices)\n",
    "            j = np.random.choice(mistake_indices)\n",
    "            w_ = w + y[j]*X[j, :]\n",
    "            h_ = np.sign(np.dot(X, w_))\n",
    "            mistake_indices_ = np.where(h_ != y)[0]\n",
    "            mistake_num_ = len(mistake_indices_)\n",
    "            if mistake_num_ <= mistake_num:\n",
    "                w = w_\n",
    "        else:\n",
    "            break\n",
    "    h = np.sign(np.dot(X, w))\n",
    "    mistake_indices = np.where(h != y)[0]\n",
    "    mistake_num = len(mistake_indices)\n",
    "    print('Initial weight vector of Pocket Algorithm is', w_init)\n",
    "    print('Final weight vector of Pocket Algorithm is', w)\n",
    "    print('Accuracy of Pocket Algorithm is %.2f%%' %\n",
    "          (100*(X.shape[0]-mistake_num)/X.shape[0]))\n",
    "    return w"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-03-23T15:16:31.992920Z",
     "start_time": "2020-03-23T15:16:28.842852Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initial weight vector of Perceptron Learning Algorithm is [-1.43026011 -1.92269115  0.69713978]\n",
      "Final weight vector of Perceptron Learning Algorithm is [-0.43026011  3.12097784  0.47082553]\n",
      "Accuracy of Perceptron Learning Algorithm is 100.00%\n",
      "Initial weight vector of Pocket Algorithm is [-1.43026011 -1.92269115  0.69713978]\n",
      "Final weight vector of Pocket Algorithm is [-2.43026011  3.84722492  0.15789058]\n",
      "Accuracy of Pocket Algorithm is 100.00%\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X1, y1 = data_generator([-5, 0], np.identity(2), [5, 0], np.identity(2), 400)\n",
    "np.random.seed()\n",
    "w_init = np.random.randn(3)\n",
    "\n",
    "w1 = perce_v1(X1, y1, w_init, MAX_ITERATION)\n",
    "w2 = perce_v2(X1, y1, w_init, MAX_ITERATION)\n",
    "drawer(X1, y1, w1, w2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-03-23T15:16:37.045462Z",
     "start_time": "2020-03-23T15:16:34.744169Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initial weight vector of Perceptron Learning Algorithm is [ 0.34873121 -0.48641155  1.1223297 ]\n",
      "Final weight vector of Perceptron Learning Algorithm is [0.34873121 3.51903438 0.45074871]\n",
      "Accuracy of Perceptron Learning Algorithm is 97.25%\n",
      "Initial weight vector of Pocket Algorithm is [ 0.34873121 -0.48641155  1.1223297 ]\n",
      "Final weight vector of Pocket Algorithm is [-0.65126879  1.99638631 -0.05015561]\n",
      "Accuracy of Pocket Algorithm is 97.50%\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X1, y1 = data_generator([-2, 0], np.identity(2), [2, 0], np.identity(2), 400)\n",
    "np.random.seed()\n",
    "w_init = np.random.randn(3)\n",
    "\n",
    "w1 = perce_v1(X1, y1, w_init, MAX_ITERATION)\n",
    "w2 = perce_v2(X1, y1, w_init, MAX_ITERATION)\n",
    "drawer(X1, y1, w1, w2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-03-23T15:16:41.670952Z",
     "start_time": "2020-03-23T15:16:39.290321Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initial weight vector of Perceptron Learning Algorithm is [-0.35135064 -1.09544497  0.37965117]\n",
      "Final weight vector of Perceptron Learning Algorithm is [-0.35135064  0.47434718  1.00382417]\n",
      "Accuracy of Perceptron Learning Algorithm is 68.00%\n",
      "Initial weight vector of Pocket Algorithm is [-0.35135064 -1.09544497  0.37965117]\n",
      "Final weight vector of Pocket Algorithm is [-0.35135064  3.38265252  0.64649513]\n",
      "Accuracy of Pocket Algorithm is 87.25%\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X1, y1 = data_generator([-1, 0], np.identity(2), [1, 0], np.identity(2), 400)\n",
    "np.random.seed()\n",
    "w_init = np.random.randn(3)\n",
    "\n",
    "w1 = perce_v1(X1, y1, w_init, MAX_ITERATION)\n",
    "w2 = perce_v2(X1, y1, w_init, MAX_ITERATION)\n",
    "drawer(X1, y1, w1, w2)"
   ]
  }
 ],
 "metadata": {
  "hide_input": false,
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
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  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
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   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
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  "varInspector": {
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   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
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    "r": {
     "delete_cmd_postfix": ") ",
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     "library": "var_list.r",
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   "oldHeight": 404.12,
   "position": {
    "height": "425.4px",
    "left": "833.36px",
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}
